June 16, 2024

Archie Wertheim

Technology Integration and Foundations for Effective Leadership

Women in AI: Miriam Vogel stresses the need for responsible AI

6 min read
Miriam Vogel


To give AI-focused women academics and others their well-deserved — and overdue — time in the spotlight, TechCrunch has been publishing a series of interviews focused on remarkable women who’ve contributed to the AI revolution. We’re publishing these pieces throughout the year as the AI boom continues, highlighting key work that often goes unrecognized. Read more profiles here.

Miriam Vogel is the CEO of EqualAI, a nonprofit created to reduce unconscious bias in AI and promote responsible AI governance. She also serves as chair to the recently launched National AI Advisory Committee, mandated by Congress to advise President Joe Biden and the White House on AI policy, and teaches technology law and policy at Georgetown University Law Center.

Vogel previously served as associate deputy attorney general at the Justice Department, advising the attorney general and deputy attorney general on a broad range of legal, policy and operational issues. As a board member at the Responsible AI Institute and senior advisor to the Center for Democracy and Technology, Vogel’s advised White House leadership on initiatives ranging from women, economic, regulatory and food safety policy to matters of criminal justice.

Briefly, how did you get your start in AI? What attracted you to the field?

I started my career working in government, initially as a Senate intern, the summer before 11th grade. I got the policy bug and spent the next several summers working on the Hill and then the White House. My focus at that point was on civil rights, which is not the conventional path to artificial intelligence, but looking back, it makes perfect sense.

After law school, my career progressed from an entertainment attorney specializing in intellectual property to engaging civil rights and social impact work in the executive branch. I had the privilege of leading the equal pay task force while I served at the White House, and, while serving as associate deputy attorney general under former deputy attorney general Sally Yates, I led the creation and development of implicit bias training for federal law enforcement.

I was asked to lead EqualAI based on my experience as a lawyer in tech and my background in policy addressing bias and systematic harms. I was attracted to this organization because I realized AI presented the next civil rights frontier. Without vigilance, decades of progress could be undone in lines of code.

I have always been excited about the possibilities created by innovation, and I still believe AI can present amazing new opportunities for more populations to thrive — but only if we are careful at this critical juncture to ensure that more people are able to meaningfully participate in its creation and development.

How do you navigate the challenges of the male-dominated tech industry, and, by extension, the male-dominated AI industry?

I fundamentally believe that we all have a role to play in ensuring that our AI is as effective, efficient and beneficial as possible. That means making sure we do more to support women’s voices in its development (who, by the way, account for more than 85% of purchases in the U.S., and so ensuring their interests and safety is incorporated is a smart business move), as well as the voices of other underrepresented populations of various ages, regions, ethnicities and nationalities who are not sufficiently participating.

As we work toward gender parity, we must ensure more voices and perspectives are considered in order to develop AI that works for all consumers — not just AI that works for the developers.

What advice would you give to women seeking to enter the AI field?

First, it is never too late to start. Never. I encourage all grandparents to try using OpenAI’s ChatGPT, Microsoft’s Copilot or Google’s Gemini. We are all going to need to become AI-literate in order to thrive in what is to become an AI-powered economy. And that is exciting! We all have a role to play. Whether you are starting a career in AI or using AI to support your work, women should be trying out AI tools, seeing what these tools can and cannot do, seeing whether they work for them and generally become AI-savvy.

Second, responsible AI development requires more than just ethical computer scientists. Many people think that the AI field requires a computer science or some other STEM degree when, in reality, AI needs perspectives and expertise from women and men from all backgrounds. Jump in! Your voice and perspective is needed. Your engagement is crucial.

What are some of the most pressing issues facing AI as it evolves?

First, we need greater AI literacy. We are “AI net-positive” at EqualAI, meaning we think AI is going to provide unprecedented opportunities for our economy and improve our daily lives — but only if these opportunities are equally available and beneficial for a greater cross-section of our population. We need our current workforce, next generation, our grandparents — all of us — to be equipped with the knowledge and skills to benefit from AI.

Second, we must develop standardized measures and metrics to evaluate AI systems. Standardized evaluations will be crucial to building trust in our AI systems and allowing consumers, regulators and downstream users to understand the limits of the AI systems they are engaging with and determine whether that system is worthy of our trust. Understanding who a system is built to serve and the envisioned use cases will help us answer the key question: For whom could this fail?

What are some issues AI users should be aware of?

Artificial intelligence is just that: artificial. It is built by humans to “mimic” human cognition and empower humans in their pursuits. We must maintain the proper amount of skepticism and engage in due diligence when using this technology to ensure that we are placing our faith in systems that deserve our trust. AI can augment — but not replace — humanity.

We must remain clear-eyed on the fact that AI consists of two main ingredients: algorithms (created by humans) and data (reflecting human conversations and interactions). As a result, AI reflects and adapts our human flaws. Bias and harms can embed throughout the AI lifecycle, whether through the algorithms written by humans or through the data that is a snapshot of human lives. However, every human touchpoint is an opportunity to identify and mitigate the potential harm.

Because one can only imagine as broadly as their own experience allows and AI programs are limited by the constructs under which they are built, the more people with varied perspectives and experiences on a team, the more likely they are to catch biases and other safety concerns embedded in their AI.

What is the best way to responsibly build AI?

Building AI that is worthy of our trust is all of our responsibility. We can’t expect someone else to do it for us. We must start by asking three basic questions: (1) For whom is this AI system built (2), what were the envisioned use cases and (3) for whom can this fail? Even with these questions in mind, there will inevitably be pitfalls. In order to mitigate against these risks, designers, developers and deployers must follow best practices.

At EqualAI, we promote good “AI hygiene,” which involves planning your framework and ensuring accountability, standardizing testing, documentation and routine auditing. We also recently published a guide to designing and operationalizing a responsible AI governance framework, which delineates the values, principles and framework for implementing AI responsibly at an organization. The paper serves as a resource for organizations of any size, sector or maturity in the midst of adopting, developing, using and implementing AI systems with an internal and public commitment to do so responsibly.

How can investors better push for responsible AI?

Investors have an outsized role in ensuring our AI is safe, effective and responsible. Investors can ensure the companies seeking funding are aware of and thinking about mitigating potential harms and liabilities in their AI systems. Even asking the question, “How have you instituted AI governance practices?” is a meaningful first step in ensuring better outcomes.

This effort is not just good for the public good; it is also in the best interest of investors who will want to ensure the companies they are invested in and affiliated with are not associated with bad headlines or encumbered by litigation. Trust is one of the few non-negotiables for a company’s success, and a commitment to responsible AI governance is the best way to build and sustain public trust. Robust and trustworthy AI makes good business sense.



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